IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i16p6086-d894788.html
   My bibliography  Save this article

Intelligent Optimization of Switched Reluctance Motor Using Genetic Aggregation Response Surface and Multi-Objective Genetic Algorithm for Improved Performance

Author

Listed:
  • Chiweta Emmanuel Abunike

    (School of Engineering, University of Aberdeen, Aberdeen AB24 3UE, UK
    Department of Electrical/Electronic Engineering, Michael Okpara University of Agriculture, Umudike 440101, Abia State, Nigeria)

  • Ogbonnaya Inya Okoro

    (Department of Electrical/Electronic Engineering, Michael Okpara University of Agriculture, Umudike 440101, Abia State, Nigeria)

  • Sumeet S. Aphale

    (School of Engineering, University of Aberdeen, Aberdeen AB24 3UE, UK)

Abstract

In this paper, a thorough framework for multiobjective design optimization of switched reluctance motor (SRM) is proposed. Selection of stator and rotor pole embrace coefficients is an essential step in the SRM design process since it influences torque output and torque ripple in SRM. The problem of determining optimal pole embrace is formulated as a multi-objective optimization problem with the objective of optimizing average torque, efficiency and torque ripple, and response surface models were obtained based on the genetic aggregation method. The results obtained by genetic aggregation response surface (GARS) and the non-dominated genetic algorithm (NSGA-II) were validated with the finite element method (FEM) model of the initial SRM. The optimized model displayed better efficiency profile over a wide speed range. The initial and optimized models recorded maximum efficiencies of 85% and 94.05%, respectively, at 2000 rpm. The efficiency values of 93.97–94.05% were achieved for the three pareto optimal candidates. The findings indicate the viability of the suggested strategy and support the use of GARS and NSGA-II as useful methods for addressing SRM key challenges.

Suggested Citation

  • Chiweta Emmanuel Abunike & Ogbonnaya Inya Okoro & Sumeet S. Aphale, 2022. "Intelligent Optimization of Switched Reluctance Motor Using Genetic Aggregation Response Surface and Multi-Objective Genetic Algorithm for Improved Performance," Energies, MDPI, vol. 15(16), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:6086-:d:894788
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/16/6086/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/16/6086/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Da-Chen Pang & Chih-Ting Wang, 2018. "A Wireless-Driven, Micro, Axial-Flux, Single-Phase Switched Reluctance Motor," Energies, MDPI, vol. 11(10), pages 1-17, October.
    2. Md Sydur Rahman & Grace Firsta Lukman & Pham Trung Hieu & Kwang-Il Jeong & Jin-Woo Ahn, 2021. "Optimization and Characteristics Analysis of High Torque Density 12/8 Switched Reluctance Motor Using Metaheuristic Gray Wolf Optimization Algorithm," Energies, MDPI, vol. 14(7), pages 1-17, April.
    3. Jingwei Zhang & Honghua Wang & Sa Zhu & Tianhang Lu, 2019. "Multi-Physics Multi-Objective Optimal Design of Bearingless Switched Reluctance Motor Based on Finite-Element Method," Energies, MDPI, vol. 12(12), pages 1-18, June.
    4. Ilka, Reza & Alinejad-Beromi, Yousef & Yaghobi, Hamid, 2018. "Cogging torque reduction of permanent magnet synchronous motor using multi-objective optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 153(C), pages 83-95.
    5. Yuanfeng Lan & Yassine Benomar & Kritika Deepak & Ahmet Aksoz & Mohamed El Baghdadi & Emine Bostanci & Omar Hegazy, 2021. "Switched Reluctance Motors and Drive Systems for Electric Vehicle Powertrains: State of the Art Analysis and Future Trends," Energies, MDPI, vol. 14(8), pages 1-29, April.
    6. Stefan Kocan & Pavol Rafajdus & Ronald Bastovansky & Richard Lenhard & Michal Stano, 2021. "Design and Optimization of a High-Speed Switched Reluctance Motor," Energies, MDPI, vol. 14(20), pages 1-23, October.
    7. Mohamed El-Nemr & Mohamed Afifi & Hegazy Rezk & Mohamed Ibrahim, 2021. "Finite Element Based Overall Optimization of Switched Reluctance Motor Using Multi-Objective Genetic Algorithm (NSGA-II)," Mathematics, MDPI, vol. 9(5), pages 1-20, March.
    8. Xing Wang & Ryszard Palka & Marcin Wardach, 2020. "Nonlinear Digital Simulation Models of Switched Reluctance Motor Drive," Energies, MDPI, vol. 13(24), pages 1-17, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vijina Abhijith & M. J. Hossain & Gang Lei & Premlal Ajikumar Sreelekha & Tibinmon Pulimoottil Monichan & Sree Venkateswara Rao, 2022. "Hybrid Switched Reluctance Motors for Electric Vehicle Applications with High Torque Capability without Permanent Magnet," Energies, MDPI, vol. 15(21), pages 1-16, October.
    2. Yun Zhang & Liang Chen & Zhixue Wang & Enguang Hou, 2022. "Speed Control of Switched Reluctance Motor Based on Regulation Region of Switching Angle," Energies, MDPI, vol. 15(16), pages 1-24, August.
    3. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    4. Mahmoud Hamouda & Fahad Al-Amyal & Ismoil Odinaev & Mohamed N. Ibrahim & László Számel, 2022. "A Novel Universal Torque Control of Switched Reluctance Motors for Electric Vehicles," Mathematics, MDPI, vol. 10(20), pages 1-21, October.
    5. Arti Aniqa Tabassum & Haeng Muk Cho & Md. Iqbal Mahmud, 2024. "Essential Features and Torque Minimization Techniques for Brushless Direct Current Motor Controllers in Electric Vehicles," Energies, MDPI, vol. 17(18), pages 1-27, September.
    6. Yuanfeng Lan & Julien Croonen & Mohamed Amine Frikha & Mohamed El Baghdadi & Omar Hegazy, 2022. "A Comprehensive Performance Comparison between Segmental and Conventional Switched Reluctance Machines with Boost and Standard Converters," Energies, MDPI, vol. 16(1), pages 1-18, December.
    7. Shantanu Pardhi & Sajib Chakraborty & Dai-Duong Tran & Mohamed El Baghdadi & Steven Wilkins & Omar Hegazy, 2022. "A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology, Hydrogen, Energy and Thermal Management Solutions," Energies, MDPI, vol. 15(24), pages 1-55, December.
    8. Mlungisi Ntombela & Kabeya Musasa, 2023. "Load Profile and Load Flow Analysis for a Grid System with Electric Vehicles Using a Hybrid Optimization Algorithm," Sustainability, MDPI, vol. 15(12), pages 1-23, June.
    9. Mingyu Choi & Gilsu Choi & Gerd Bramerdorfer & Edmund Marth, 2022. "Systematic Development of a Multi-Objective Design Optimization Process Based on a Surrogate-Assisted Evolutionary Algorithm for Electric Machine Applications," Energies, MDPI, vol. 16(1), pages 1-19, December.
    10. Jiongjiong Cai & Peng Ke & Xiao Qu & Zihui Wang, 2022. "Research on the Design of Auxiliary Generator for Enthalpy Reduction and Steady Speed Scroll Expander," Energies, MDPI, vol. 15(9), pages 1-17, April.
    11. Weihua Qian & Hang Xu & Houjin Chen & Lvqing Yang & Yuanguo Lin & Rui Xu & Mulan Yang & Minghong Liao, 2024. "A Synergistic MOEA Algorithm with GANs for Complex Data Analysis," Mathematics, MDPI, vol. 12(2), pages 1-30, January.
    12. Yuanfeng Lan & Mohamed Amine Frikha & Julien Croonen & Yassine Benômar & Mohamed El Baghdadi & Omar Hegazy, 2022. "Design Optimization of a Switched Reluctance Machine with an Improved Segmental Rotor for Electric Vehicle Applications," Energies, MDPI, vol. 15(16), pages 1-16, August.
    13. Christodoulos Katis & Athanasios Karlis, 2023. "Evolution of Equipment in Electromobility and Autonomous Driving Regarding Safety Issues," Energies, MDPI, vol. 16(3), pages 1-34, January.
    14. Mahmoud A. Gaafar & Arwa Abdelmaksoud & Mohamed Orabi & Hao Chen & Mostafa Dardeer, 2021. "Performance Investigation of Switched Reluctance Motor Driven by Quasi-Z-Source Integrated Multiport Converter with Different Switching Algorithms," Sustainability, MDPI, vol. 13(17), pages 1-14, August.
    15. Grace Firsta Lukman & Xuan Son Nguyen & Jin-Woo Ahn, 2020. "Design of a Low Torque Ripple Three-Phase SRM for Automotive Shift-by-Wire Actuator," Energies, MDPI, vol. 13(9), pages 1-13, May.
    16. Vladimir Kindl & Tomas Kavalir & Jiri Sika & Jan Hnatik & Michal Krizek & Michal Frivaldsky, 2022. "Wireless Power Transmission System for Powering Rotating Parts of Automatic Machineries," Energies, MDPI, vol. 15(18), pages 1-15, September.
    17. Jean-Michel Grenier & Ramón Pérez & Mathieu Picard & Jérôme Cros, 2021. "Magnetic FEA Direct Optimization of High-Power Density, Halbach Array Permanent Magnet Electric Motors," Energies, MDPI, vol. 14(18), pages 1-19, September.
    18. Ryszard Palka & Marcin Wardach, 2022. "Design and Application of Electrical Machines," Energies, MDPI, vol. 15(2), pages 1-7, January.
    19. Yawei Wang & Nicola Bianchi & Ronghai Qu, 2022. "Comparative Study of Non-Rare-Earth and Rare-Earth PM Motors for EV Applications," Energies, MDPI, vol. 15(8), pages 1-18, April.
    20. Xinming Xu & Yang Gu & Guangjun Liu, 2022. "Study on a Wheel Electric Drive System with SRD for Loader," Energies, MDPI, vol. 15(10), pages 1-16, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:6086-:d:894788. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.